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Use of knowledge based systems for the detection and monitoring of unplanned developments / Faith Njoki Karanja (2002)
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Titre : Use of knowledge based systems for the detection and monitoring of unplanned developments Type de document : Thèse/HDR Auteurs : Faith Njoki Karanja, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2002 Collection : DGK - C Sous-collection : Dissertationen num. 558 Importance : 107 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-9597-7 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aide à la décision
[Termes IGN] base de connaissances
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] image satellite
[Termes IGN] interprétation automatique
[Termes IGN] modélisation
[Termes IGN] photo-interprétation
[Termes IGN] prospective
[Termes IGN] représentation graphique
[Termes IGN] simulation
[Termes IGN] surveillance de l'urbanisation
[Termes IGN] système à base de connaissances
[Termes IGN] système d'information géographique
[Termes IGN] traitement d'image
[Termes IGN] zone urbaineRésumé : (Auteur) Within the context of an urban land use, two general status can be distinguished namely developed land (residential, industrial area, construction area, etc), and reserved land (forest, water bodies, garden, parks, open area etc). However, not all developed land is legal or formal a phenomena prevalent in developing countries. For the planners it is important to have the capacity to detect, localise and predict the trend of this phenomenon in order to facilitate reaction planning. In this regard, the main objective of this study is to develop a methodology that exploits existing planning data and urban land use drivers in combination with remotely sensed imagery for the detection and quantification of unplanned developments and subsequently facilitate in monitoring their trends. Since planning is a continuous process, remotely sensed data lends itself to a good source of information pertaining to the extent of developed and reserved areas at any given epoch. The methodology has been subdivided into four modules, namely the interpretation, detection, trend prediction and the evaluation.
Knowledge based image interpretation, namely rule based system was employed in the extraction of developed and reserved areas from multispectral image data. As input into the interpretation process four images cues i.e. NDVI, Texture, Edge Density, and unsupervised classification have been tested. Experience has shown that data reduction and refinement prior to its incorporation in the knowledge base enables few rules to be established and thereby minimising rule correlation. However, knowledge representation is a challenge and especially when it involves rules association. Acceptable results have been obtained which imply that such a technique is promising. Additional information e.g. GIS data would nevertheless be useful as a guide in the extraction of objects like parking areas and some complex built up areas (e.g. buildings), roads, etc thus improving the results.
For the detection of unplanned developments, the constraints of planning data have been exploited. Specifically, planning data has been used in combination with remotely sensed data depicting As It Were situation to generate As It Should Be scenario with specific emphasis on the new legal/allowable developments. This formed a backdrop for the detection of unplanned developments, which essentially translates to the difference between the As It Should Be situation and As It IS within the planning and implementation time frame. Prototype experiments carried out show that this is a feasible technique and can easily be implemented for fast detection in comparison to the current ad hoc field techniques.
In the trend prediction of unplanned developments, land use drivers based on compatibility of land uses, transport network, and hydrography sources are used to establish their influence on the new developed areas. Results show that existing land uses influence highly new developed areas. A combination effect of these influences (land use drivers) when employed results in stratification of pressure zones into fuzzy blocks ranging from those which are likely to undergo extensions of unplanned developments to those which are unlikely. Such information could enable planners develop a program in preparation for such eventualities and priorities areas that require urgent reaction planning.
For the evaluation of the results, both qualitative and quantitative evaluation techniques have been tested namely visual comparison, polygonpixel count and kappa index. Comparable results have been obtained based on these three techniques for the interpretation and detection modules. The choice of which technique to apply depends on the application and the level of detail required.
In conclusion, this study has demonstrated that a 'complete package' that will enable planners to detect and predict the trend of unplanned developments is feasible. In order to ensure success, planning should be viewed as a collective responsibility, where all stakeholders are participants. Further, sound land law system that ensures land accessibility and security of tenure as well as promotes transparency in land allocation issues should be implemented and enforced.Numéro de notice : 15027 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère En ligne : https://d-nb.info/966084659/34 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55045 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 15027-02 35.46 Livre Centre de documentation Télédétection Disponible 15027-01 35.46 Livre Centre de documentation Télédétection Disponible
Titre : Workshop 12 Knowledge discovery from temporal and spatial data Type de document : Actes de congrès Auteurs : Christophe Dousson, Éditeur scientifique ; Franck Höppner, Éditeur scientifique ; René Quiniou, Éditeur scientifique Editeur : Lyon : Université de Lyon 1 Claude Bernard Année de publication : 2002 Conférence : ECAI 2002, 15th European Conference on Artificial Intelligence 21/07/2002 26/07/2002 Lyon France Proceedings ACM Importance : 84 p. Format : 21 x 30 cm Note générale : Workshop organisé dans le cadre de ECAI 2002, 15th European Conference on Artificial Intelligence, à Lyon en juillet 2002 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage automatique
[Termes IGN] classification dirigée
[Termes IGN] découverte de connaissances
[Termes IGN] données médicales
[Termes IGN] données spatiotemporelles
[Termes IGN] extraction de données
[Termes IGN] médecine humaine
[Termes IGN] modèle conceptuel de flux
[Termes IGN] reconnaissance automatique
[Termes IGN] santé
[Termes IGN] série temporelle
[Termes IGN] taxinomieIndex. décimale : CG2002 Actes de congrès en 2002 Numéro de notice : 25351 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Actes Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93691 Voir aussiRéservation
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Code-barres Cote Support Localisation Section Disponibilité 25351-01 CG2002 Livre Centre de documentation Congrès Disponible Mapping wildfire burns severity in southern California forests and shrub lands using enhanced Thematic Mapper imagery / J. Rogan in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)
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Titre : Mapping wildfire burns severity in southern California forests and shrub lands using enhanced Thematic Mapper imagery Type de document : Article/Communication Auteurs : J. Rogan, Auteur ; Janet Franklin, Auteur Année de publication : 2001 Article en page(s) : pp 89 - 99 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multibande
[Termes IGN] carte de la végétation
[Termes IGN] cartographie thématique
[Termes IGN] classification
[Termes IGN] image Landsat-ETM+
[Termes IGN] incendie de forêt
[Termes IGN] risque naturelRésumé : (Auteur) Wildfire is a major disturbance agent in Mediterranean Type Ecosystems (MTEs). Providing reliable, quantitative information on the area of burns and the level of damage caused is therefore important both for guiding resource management and global change monitoring. Previous studies have successfully mapped burn severity using remote sensing, but reliable accuracy has yet to be gained using standard methods over different vegetation types. The objective of this research was to classify burn severity across several vegetation types using Landsat ETM imagery in two areas affected by wildfire in southern California in June 1999. Spectral mixture analysis (SMA) using four reference endmembers (vegetation, soil, shade, non-photosynthetic vegetation) and a single (charcoal-ash) image endmember were used to enhance imagery prior to burn severity classification using decision trees. SMA provided a robust technique for enhancing fire-affected areas due to its ability to extract sub~pixel information and minimize the effects of topography on single date satellite data. Overall kappa classification accuracy results were high (0. 71 and 0.85, respectively)jor the burned areas, using five canopy consumption classes. Individual severity class accuracies ranged from 0.5 to 0.94. Numéro de notice : A2002-041 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040108542218 En ligne : https://doi.org/10.1080/10106040108542218 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21958
in Geocarto international > vol 16 n° 4 (December 2001 - February 2002) . - pp 89 - 99[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-01041 RAB Revue Centre de documentation En réserve L003 Disponible Revealing the anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the greater Cairo region, Egypt / T. Rashed in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)
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Titre : Revealing the anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the greater Cairo region, Egypt Type de document : Article/Communication Auteurs : T. Rashed, Auteur ; J.R. Weeks, Auteur ; M.S. Gadalla, Auteur ; A. Hill, Auteur Année de publication : 2001 Article en page(s) : pp 5 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] Egypte
[Termes IGN] image multibande
[Termes IGN] milieu urbain
[Termes IGN] occupation du solRésumé : (Auteur) This paper examines the feasibility of spectral mixture analysis (SMA) in deriving comparable physical measures of urban land cover that describe the morphological characteristics of cities. SMA offers a way of analyzing satellite imagery of urban areas that may be superior to more standard methods of classification. Mixing models are based on the assumption that the remotely measured spectrum of a given pixel can be modeled as a combination of pure spectra, called endmembers. SMA, using four image endmembers (vegetation, impervious surface, soil, and shade), was applied to an IRS-1C multispectral image in order to extract measures that describe the anatomy of the Greater Cairo region, Egypt, in terms of endmember fractions. The resulting fractions were then used to classify the urban scene into eight classes of natural and human-built features through a decision tree (DT) classifier. The accuracy of the DT classification was compared to the accuracies of two per-pixel supervised classifications of the IRS-1C image employing maximum likelihood (ML) and minimum distance-to-means (MDM) classifiers. Overall KAPPA accuracies were 0. 88 for the DT classification based on SMA fractions, and 0.60 and 0.45 for the classifications conducted through ML and MDM respectively. Numéro de notice : A2002-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040108542210 En ligne : https://doi.org/10.1080/10106040108542210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21955
in Geocarto international > vol 16 n° 4 (December 2001 - February 2002) . - pp 5 - 15[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-01041 RAB Revue Centre de documentation En réserve L003 Disponible A robust texture analysis and classification approach for urban land-use and land-cover feature discrimination / S.W. Myint in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)
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Titre : A robust texture analysis and classification approach for urban land-use and land-cover feature discrimination Type de document : Article/Communication Auteurs : S.W. Myint, Auteur Année de publication : 2001 Article en page(s) : pp 27 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] analyse discriminante
[Termes IGN] analyse texturale
[Termes IGN] base de données d'occupation du sol
[Termes IGN] image multibande
[Termes IGN] méthode robuste
[Termes IGN] occupation du sol
[Termes IGN] photo-interprétation
[Termes IGN] reconnaissance d'objets
[Termes IGN] transformation en ondelettes
[Termes IGN] utilisation du solRésumé : (Auteur) Attempts to analyze urban features and to classify land use and land cover directly from high-resolution satellite data with traditional computer classification techniques have proven to be inefficient for two primary reasons. First, urban landscapes are composed of complex features. Second, traditional classifiers employ spectral information based on single pixel value and ignore a great amount of spatial information. Texture plays an important role in image segmentation and object recognition, as well as in interpretation of images in a variety of applications. This study analyzes urban texture features in multi-spectral image data. Recent developments in the very powerful mathematical theory of wavelet transforms have received overwhelming attention by image analysts. An evaluation of the ability of wavelet transform in urban feature extraction and classification was performed in this study, with six types of urban land cover features classified. The preliminary results of this research indicate that the accuracy of texture analysis in classifying urban features in fine resolution image data could be significantly improved with the use of wavelet transform approach. Numéro de notice : A2002-039 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040108542212 En ligne : https://doi.org/10.1080/10106040108542212 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21956
in Geocarto international > vol 16 n° 4 (December 2001 - February 2002) . - pp 27 - 38[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-01041 RAB Revue Centre de documentation En réserve L003 Disponible Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)
PermalinkA system for the automatic selection of conspicuous color sets for qualitative data display / P. Campadelli in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)
PermalinkDéfinition et identification d'objets sur une image à haute résolution spatiale : Application à la différenciation de types de châtaigneraies / Muriel Bonin in Ingénieries : eau, agriculture, territoires, n° 27 (septembre 2001)
PermalinkGénéralisation de l'algorithme de Douglas et Peucker pour des applications cartographiques / Xavier Barillot in Bulletin du comité français de cartographie, n°s 169 - 170 (septembre 2001 - février 2002)
PermalinkBest-bases feature extraction algorithms for classification of hyperspectral data / Satish Kumar in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
PermalinkClustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery / C.C. Funk in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
PermalinkÉtude de treillis de relations topologiques pour l'interprétation d'images satellitaires / Florence Le Ber in Revue internationale de géomatique, vol 11 n° 2 (juin - aout 2001)
PermalinkReconnaissance de patterns par réseaux de neurones / M.K. Allouche in Revue internationale de géomatique, vol 11 n° 2 (juin - aout 2001)
PermalinkKnowledge-based multivariate GIS application in environmental modeling / R.S. Ofren in Geocarto international, vol 16 n° 1 (March - May 2001)
PermalinkApport de l'imagerie satellite dans la réalisation des plans d'aménagement forestier / Nicolas Bellaiche (2001)
PermalinkPermalinkDetection of storm losses in alpine forest areas by different methodical approaches using high-resolution satellite data [pixel-based classification and object-oriented classification] / Marcel Schwarz (2001)
PermalinkEtude test sur l'estimation des superficies agricoles à partir d'images Landsat / Olivier Laporte (2001)
PermalinkGeneralization of the "Douglas and Peucker" algorithm for cartographic applications / Xavier Barillot (2001)
PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkParticipation à l'analyse des séries temporelles du système international de référence terrestre ITRS / G. Moujally (2001)
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